Changelog
Source:NEWS.md
Rogue v2.2.0 (2026-03-20)
CRAN release: 2026-03-25
Performance
TipInstability()operates on the lower triangle of distance matrices only, halving the work for row statistics (rowMads,rowVars,rowMedians).New batch C function
LOG_GRAPH_GEODESIC_MULTIcomputes log-geodesic distances for all trees in a single.Call(), reusing one interim buffer and returning lower-triangle entries directly.Cache-friendly extraction loop in
graph_geodesic.c(stride-1 access instead of stride-all_nodes).Auto-enable OpenMP parallelism in Rfast operations (
rowMads,rowVars) when the distance matrix exceeds 1 000 rows.Use
Rfast::rowMedians()in place ofmatrixStats::rowMedians().RogueTaxa()now calls.PrepareTrees()once and passes.prepared = TRUEtoQuickRogue()/Roguehalla(), avoiding redundant tree preparation.QuickRogue()precomputes information upper bounds for all iterations rather than recomputing each step.
Rogue v2.1.7 (2025-07-01)
CRAN release: 2025-07-01
Improve tip instability calculation in identical tree sets (#29).
Improve variable protection.
Rogue v2.1.6 (2023-11-29)
CRAN release: 2023-11-29
- Legend annotations in documentation.
- Disable parallel evaluation by default in
TipInstability(), addingparallelparameter to allow user to override. - Use format string in REprintf().
Rogue v2.1.4 (2023-01-16)
CRAN release: 2023-01-16
C2X compliant function prototypes.
Remove unused
sprintf()calls.
Rogue v2.1.3 (2022-09-26)
CRAN release: 2022-09-26
-
ColByStability()gainspalargument to allow specification of custom palettes.
Rogue v2.1.2 (2022-08-16)
CRAN release: 2022-08-16
Faster rogue detection when edge lengths provided, per report by Joe Keating.
Don’t list
neverDropinQuickRogue(fullSeq = TRUE).
Rogue v2.1.0 (2022-01-13)
CRAN release: 2022-01-13
Early termination of
QuickRogue()when no further improvement possible.Cophenetic()renamed to the more accurateGraphGeodesic().Calculate information content of consensus trees with p > 0.5 (#15).
Improve support for
multiPhyloobjects.New vignette detailing rogue detection with Bayesian tree samples.